CRISPR-based oligo recombineering prioritizes apicomplexan cysteines for drug discovery.

Nucleophilic amino acids are important in covalent drug development yet underutilized as anti-microbial targets. Chemoproteomic technologies have been developed to mine chemically accessible residues via their intrinsic reactivity towards electrophilic probes but cannot discern which chemically reactive sites contribute to protein function and should therefore be prioritized for drug discovery. To address this, we have developed a CRISPR-based oligo recombineering (CORe) platform to support the rapid identification, functional prioritization and rational targeting of chemically reactive sites in haploid systems. Our approach couples protein sequence and function with biological fitness of live cells. Here we profile the electrophile sensitivity of proteinogenic cysteines in the eukaryotic pathogen Toxoplasma gondii and prioritize functional sites using CORe. Electrophile-sensitive cysteines decorating the ribosome were found to be critical for parasite growth, with target-based screening identifying a parasite-selective anti-malarial lead molecule and validating the apicomplexan translation machinery as a target for ongoing covalent ligand development.

PROTACs, molecular glues and bifunctionals from bench to bedside: Unlocking the clinical potential of catalytic drugs.

The vast majority of currently marketed drugs rely on small molecules with an 'occupancy-driven' mechanism of action (MOA). Therefore, the efficacy of these therapeutics depends on a high degree of target engagement, which often requires high dosages and enhanced drug exposure at the target site, thus increasing the risk of off-target toxicities (Churcher, 2018 [1]). Although small molecule drugs have been successfully used as treatments for decades, tackling a variety of disease-relevant targets with a defined binding site, many relevant therapeutic targets remain challenging to drug due, for example, to lack of well-defined binding pockets or large protein-protein interaction (PPI) interfaces which resist interference (Dang et al., 2017 [2]). In the quest for alternative therapeutic approaches to address different pathologies and achieve enhanced efficacy with reduced side effects, ligand-induced targeted protein degradation (TPD) has gained the attention of many research groups both in academia and in industry in the last two decades. This therapeutic modality represents a novel paradigm compared to conventional small-molecule inhibitors. To pursue this strategy, heterobifunctional small molecule degraders, termed PROteolysis TArgeting Chimeras (PROTACs) have been devised to artificially redirect a protein of interest (POI) to the cellular protein homeostasis machinery for proteasomal degradation (Chamberlain et al., 2019 [3]). In this chapter, the development of PROTACs will first be discussed providing a historical perspective in parallel to the experimental progress made to understand this novel therapeutic modality. Furthermore, common strategies for PROTAC design, including assays and troubleshooting tips will be provided for the reader, before presenting a compendium of all PROTAC targets reported in the literature to date. Due to the recent advancement of these molecules into clinical trials, consideration of pharmacokinetics and pharmacodynamic properties will be introduced, together with the biotech landscape that has developed from the success of PROTACs. Finally, an overview of subsequent strategies for targeted protein degradation will be presented, concluding with further scientific quests triggered by the invention of PROTACs.

Potent and specific inhibition of the biological activity of the type-II transmembrane serine protease matriptase by the cyclic microprotein MCoTI-II.

Matriptase is a type-II transmembrane serine protease involved in epithelial homeostasis in both health and disease, and is implicated in the development and progression of a variety of cancers. Matriptase mediates its biological effects both via as yet undefined substrates and pathways, and also by proteolytic cleavage of a variety of well-defined protein substrates, several of which it shares with the closely-related protease hepsin. Development of targeted therapeutic strategies will require discrimination between these proteases. Here we have investigated cyclic microproteins of the squash Momordica cochinchinensis trypsin-inhibitor family (generated by total chemical synthesis) and found MCoTI-II to be a high-affinity (Ki 9 nM) and highly selective (> 1,000-fold) inhibitor of matriptase. MCoTI-II efficiently inhibited the proteolytic activation of pro-hepatocyte growth factor (HGF) by matriptase but not by hepsin, in both purified and cell-based systems, and inhibited HGF-dependent cell scattering. MCoTI-II also selectively inhibited the invasion of matriptase-expressing prostate cancer cells. Using a model of epithelial cell tight junction assembly, we also found that MCoTI-II could effectively inhibit the re-establishment of tight junctions and epithelial barrier function in MDCK-I cells after disruption, consistent with the role of matriptase in regulating epithelial integrity. Surprisingly, MCoTI-II was unable to inhibit matriptase-dependent proteolytic activation of prostasin, a GPI-anchored serine protease also implicated in epithelial homeostasis. These observations suggest that the unusually high selectivity afforded by MCoTI-II and its biological effectiveness might represent a useful starting point for the development of therapeutic inhibitors, and further highlight the role of matriptase in epithelial maintenance.

Protein multi-scale organization through graph partitioning and robustness analysis: application to the myosin-myosin light chain interaction.

Despite the recognized importance of the multi-scale spatio-temporal organization of proteins, most computational tools can only access a limited spectrum of time and spatial scales, thereby ignoring the effects on protein behavior of the intricate coupling between the different scales. Starting from a physico-chemical atomistic network of interactions that encodes the structure of the protein, we introduce a methodology based on multi-scale graph partitioning that can uncover partitions and levels of organization of proteins that span the whole range of scales, revealing biological features occurring at different levels of organization and tracking their effect across scales. Additionally, we introduce a measure of robustness to quantify the relevance of the partitions through the generation of biochemically-motivated surrogate random graph models. We apply the method to four distinct conformations of myosin tail interacting protein, a protein from the molecular motor of the malaria parasite, and study properties that have been experimentally addressed such as the closing mechanism, the presence of conserved clusters, and the identification through computational mutational analysis of key residues for binding.